1. Field of the Invention
The present invention relates to a random number generating device.
2. Related Background Art
As a result of the improvement in information communication networks, such as Internet, commercial transactions such as bank payments are carried out through information communication networks. As such opportunities increase, a demand for higher security arises, resulting in that various kinds of cryptosystems are developed.
In such cryptosystems, it is necessary to generate high-quality random numbers in order to improve the security level. The term “high-quality” means that there is no periodicity in random numbers, that it is impossible to predict the random numbers, etc.
Conventionally, random numbers have been generated by the use of calculating software such as a shift register. However, since the random number generated in such a manner are pseudo-random numbers, if there are considerably many numbers, a periodicity appears, thereby decreasing the security level.
In order to generate high-quality true random numbers, there are methods in which physical random numbers are generated based on physical phenomena such as thermal noises. Such physical random numbers are true random numbers in principle. Therefore, these methods are ultimate methods of generating random numbers.
A device generating random numbers by amplifying thermal noise signals of a diode is proposed in the above-described methods. In this device, a very subtle thermal noise of the diode is amplified by using various kinds of amplifiers. Accordingly, in order to generate high-quality random numbers, the circuit size inevitably becomes large.
Further, in this device, random numbers should be generated based on the diode current/voltage characteristics. Accordingly, the outputs are often biased.
Moreover, as the processing speed of semiconductor chips is increased, the speed at which random numbers are generated should also be increased.
Thus, conventional random number generating devices have problems in that the circuit size there of is large, and the outputs thereof are biased.